{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-09-08T10:33:46.178802Z",
     "start_time": "2025-09-08T10:33:45.186847Z"
    }
   },
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# 设置中文字体\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei', 'Microsoft YaHei', 'DejaVu Sans']  # 黑体、微软雅黑\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 解决负号显示问题\n",
    "path = 'D:/2506A/monty03/day11/file/'"
   ],
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 填充",
   "id": "77b4734f80779e04"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 1. 线条填充",
   "id": "3f2526e74b72ecb9"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-09-08T10:38:02.523194Z",
     "start_time": "2025-09-08T10:38:02.453776Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# plt.axhline(y=0.2,linewidth=1,color='r',linestyle='-') # 横向\n",
    "# plt.axvline(x=0.5,linewidth=1,color='r',linestyle='-') # 纵向\n",
    "\n",
    "# plt.axhline(y=0.2,xmin=0,xmax=0.5,linewidth=1,color='r',linestyle='--')\n",
    "# plt.axvline(x=0.5,ymin=0,ymax=0.5,linewidth=1,color='r',linestyle='--')\n",
    "\n",
    "plt.axhspan(0.3,0.5,color = 'r')\n",
    "plt.axvspan(0.3,0.5,color = 'g')\n",
    "\n",
    "plt.ylim(0,2)\n",
    "plt.xlim(0,2)\n",
    "\n",
    "plt.show()"
   ],
   "id": "c561b8ade4906a45",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 16
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "",
   "id": "3d5e5576901277ba"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
